Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Zelensky
Caution! Due to inherent human biases, it may seem that reports on articles aligning with our views are crafted by opponents. Conversely, reports about articles that contradict our beliefs might seem to be authored by allies. However, such perceptions are likely to be incorrect. These impressions can be caused by the fact that in both scenarios, articles are subjected to critical evaluation. This report is the product of an AI model that is significantly less biased than human analyses and has been explicitly instructed to strictly maintain 100% neutrality.
Nevertheless, HonestyMeter is in the experimental stage and is continuously improving through user feedback. If the report seems inaccurate, we encourage you to submit feedback , helping us enhance the accuracy and reliability of HonestyMeter and contributing to media transparency.
Use of exciting or shocking stories at the expense of accuracy, to provoke public interest or excitement.
The article emphasizes Biden's 'galling gaffe' and 'growing questions about his cognitive fitness', which sensationalizes the event and casts doubt on Biden's capabilities.
Provide a neutral description of the event without using charged language such as 'galling gaffe'.
Use of language that implies judgment or conveys an unbalanced viewpoint.
Terms like 'galling gaffe' and 'disastrous debate performance' convey a negative bias against Biden.
Use neutral language to describe the events and Biden's performance.
Claims made without providing evidence or support.
The article states 'Biden, who is facing growing questions about his cognitive fitness', without providing evidence or sources for these 'growing questions'.
Cite sources or provide evidence for claims regarding Biden's cognitive fitness.
- This is an EXPERIMENTAL DEMO version that is not intended to be used for any other purpose than to showcase the technology's potential. We are in the process of developing more sophisticated algorithms to significantly enhance the reliability and consistency of evaluations. Nevertheless, even in its current state, HonestyMeter frequently offers valuable insights that are challenging for humans to detect.